Paper presented at the 2015 Science and Technology Indicators (STI) Conference, 2-4 September 2015, Lugano, Switzerland

1. What is an emerging technology?
Science and Technology Indicators Conference – 2-4 September 2015, Lugano
Rotolo Daniele1,2, Diana Hicks2, Ben Martin1,3
1 SPRU (Science Policy Research Unit), University of Sussex
2 Schoolof Public Policy, Georgia Institute of Technology
3 Centre for Science and Policy (CSAP) and Centrefor BusinessResearch,
Judge BusinessSchool, University of Cambridge

2. The growing interest in emerging technologies

3. The growing interest in emerging technologies
Source: Authors’ elaboration
Year
Numberofpublications
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1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
050100150200250300
Year
0500100015002000250030003500
Numberofnewsarticles
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Publications in all disciplines
Publications in social sciences
News articles

4. The growing interest in emerging technologies… Why?
Emerging technologies are conceived as new technologies
with the potential to change the status quo

5. The problem
Growing interest, but no consensus on what qualifies a technology to be ‘emergent’
• Proposed definitions overlap, but also point to different characteristics
o extensive socio-economic impact (e.g. Porter et al., 2002)
o long term impact (15-year horizon or so) (Porter et al., 2002)
o uncertainty (Boon & Moors, 2008)
o novelty and growth (Small et al., 2014)
• A variety of methodological approaches has been developed, especially in scientometrics, for the
detection and analysis of emergence in science and technology
• These methods however build on relatively loose definitions of emerging technologies or often no
definition at all is provided – methods tend to greatly differ also with the use of the same or similar
techniques

6. Research aim
To develop a definition of ‘emerging technologies’ and
a framework for their operationalisation

7. Defining emerging technologies

8. Defining emerging technologies
To develop a definition of ‘emerging technology’ our approach builds on:
1.The examination of the concept of emergence
2.The review of major innovation studies focused on technological emergence

9. 1. The concept of emergence
Table 1: Dictionary definition of emerge/emergent.
Dictionary definition of ”emerge”/”emergent” Attributes/features
”the process of coming into being, or of becoming important and promi-
nent” (New Oxford American Dictionary)
important; prominent
”to become manifest: become known [...]” (Merriam-Webster’s Colle-
giate Dictionary)
become manifest; become known
”to rise up or come forth [...] to become evident [...] to come into
existence” (The American Heritage Desk Dictionary and Thesaurus)
evident; come into existence
”move out of something and become visible [...] come into existence or
greater prominence [...] become known [...] i the process of coming into
being or prominence” (Concise Oxford English Dictionary)
visible; prominent; become known;
come into being
”starting to exist or to become known [...] to appear by coming out
of something or out from behind something (Cambridge Dictionaries
Online)
become known; to appear
Source: search performed by authors on major English dictionaries.
2 The concept of emergence

10. 2. Review of innovation studies
• We searched for ”emerg* technolog*”,
”tech* emergence”, ”emergence of*
technolog*” or ”emerg* scien* technol*”
in publication titles (SCOPUS)
• 2,201 publications were identified of
which 501 in social science domains
• ~ 50% of these were not relevant (focus
on specific industrial context or on the
educational sector)
• A core set of 12 studies that contributed
to the conceptualisation of technological
emergence was identified
Study Domain Definition (elaborated or adopted)
Martin (1995) S&T policy ”A ’generic emerging technology’ is defined [...] as a technology the
exploitation of which will yield benefits for a wide range of sectors of
the economy and/or society” (p. 165)
Day and
Schoemaker
(2000)
Management ”emerging technologies as science-based innovation that have the po-
tential to create a new industry or transform an existing ones. They
include discontinuous innovations derived from radical innovations [...]
as well as more evolutionary technologies formed by the convergence of
previously separate research streams” (p. 30)
Porter et al.
(2002)
S&T policy ”Emerging technologies are defined here as those that could exert much
enhanced economic influence in the coming (roughly) 15-year horizon.”
(p. 189)
Corrocher
et al. (2003)
Evolutionary
economics
”The emergence of a new technology is conceptualised [...] as an evo-
lutionary process of technical, institutional and social change, which
occurs simultaneously at three levels: the level of individual firms or
research laboratories, the level of social and institutional context, and
the level of the nature and evolution of knowledge and the related tech-
nological regime.” (p. 4)
Hung and
Chu (2006)
S&T policy ”Emerging technologies are the core technologies, which have not yet
demonstrated potential for changing the basis of competition” (p. 104)
Boon and
Moors (2008)
S&T policy ”Emerging technologies are technologies in an early phase of develop-
ment. This implies that several aspects, such as the characteristics of
the technology and its context of use or the configuration of the actor
network and their related roles are still uncertain and non-specific” (p.
1915)
Srinivasan
(2008)
Management ”I conceptualize emerging technologies in terms of three broad sub-
heads: their sources (where do emerging technologies come from?),
their characteristics (what defines emerging technologies?) and their
e↵ects (what are the e↵ects of emerging technologies on firms’ strate-
gies and outcomes?).” (p. 634)
Cozzens et al.
(2010)
S&T policy ”Emerging technology — a technology that shows high potential but
hasn’t demonstrated its value or settled down into any kind of consen-
sus.” (p. 364) ”The concepts reflected in the definitions of emerging
technologies, however, can be summarised four-fold as follows: (1) fast
recent growth; (2) in the process of transition and/or change; (3) mar-
ket or economic potential that is not exploited fully yet; (4) increasingly
science-based.” (p. 366)
Stahl (2011) S&T policy ”[...] emerging technologies are defined as those technologies that have
the potential to gain social relevance within the next 10 to 15 years.
This means that they are currently at an early stage of their develop-
ment process. At the same time, they have already moved beyond the
purely conceptual stage. [...] Despite this, these emerging technologies
are not yet clearly defined. Their exact forms, capabilities, constraints,
and uses are still in flux” (p. 3-4)
Alexander
et al. (2012)
S&T policy ”Technical emergence is the phase during which a concept or construct
is adopted and iterated by [...] members of an expert community of
practice, resulting in a fundamental change in (or significant extension
of) human understanding or capability.” (p. 1289)
Halaweh
(2013)
Management Characteristics of (IT) emerging technologies ”are uncertainty, network
e↵ect, unseen social and ethical concerns, cost, limitation to particular
countries, and a lack of investigation and research.” (p. 108)
Small et al.
(2014)
Scientometrics ”[...] there is nearly universal agreement on two properties associated
with emergence — novelty (or newness) and growth.” (p. 2)

11. Attributes of emergence
2. Review of innovation studies
We analysed the textual content of the proposed definitions to extract all the componentconcepts
and grouped those into attributes of emergence
Table 4: Attributes of emergence and reviewed key innovation studies.
Innovation studies defining emerging technologies
Attribute of emergence
Martin(1995)
DayandSchoemaker(2000)
Porteretal.(2002)
Corrocheretal.(2003)
HungandChu(2006)
BoonandMoors(2008)
Srinivasan(2008)
Cozzensetal.(2010)
Stahl(2011)
Alexanderetal.(2012)
Halaweh(2013)
Smalletal.(2014)
Radical novelty x x x
Relatively fast growth x x x
Coherence x x x x
Prominent impact x x x x x x x x x
Uncertainty and ambiguity x x x x x x x
Source: authors’ elaboration.
domain in which it is arising. However, the impact the technology can exert on that domain is

12. Radical novelty
• Included in 2/12 definitions: ”novelty (or newness)” (Small et al., 2014),”discontinuous
innovations derived from radical innovations” (Day & Schoemaker, 2000)
• To achieve a new or a changed purpose/function, emerging technologies build on different
basic principles (e.g. cars with an internal combustion engine vs. an electric engine) (Arthur,
2007)
• Revolutionary/evolutionary technologies and radical novelty (see Adner & Levinthal, 2002)
o ‘Revolutionary’ – technologies with relatively limited prior developments (nano-
materials, DNA sequencing)
o ‘Evolutionary’ – niches and speciation process (e.g. wireless communication
technology), but also incremental technological advances
• ‘Novelty’ vs. ‘radical novelty’

13. Relatively fast growth
• Included in 3/12 definitions:
”fast clock speed” (Srinivasan,
2008) or ”fast growth” (Cozzens et
al., 2010), or ”growth” (Small et al.,
2014)
• Growth may be observed
across a number of
dimensions (e.g. actors,
public and private funding,
publications, patents,
prototypes, products)
• The context matters: A
technology may grow rapidly
in comparison with other
technologies in the same
domain(s) which may be
growing at a slower pace Source: Consumer Electronic Association(2011)

14. Coherence
• Included in 4/12 definitions: ”convergence of previously separated research streams” (Day &
Schoemaker, 2000), ”convergence in technologies” (Srinivasan, 2008), technologies that ”have
already moved beyond the purely conceptual stage” (Stahl, 2011)
• Also as arising of ”an expert community of practice” that adopts and iterates the concepts
or constructs”(Alexander et al., 2012)
o Both a number of people and a professional connection between those people are
necessary – coherence refers to internal characteristics of a group such as ’sticking
together’, ’being united’, ’logical inter- connection’ and ’congruity’
o The status of external relations is also important – the emerging technology must
detach itself from its technological ’parents’ to some degree to merit a separate
identity (Glanzel and Thijs, 2012)

15. Prominent impact
• Included in 9/12 definitions: ”benefits for a wide range of sectors” (Martin, 1995),
”create new industry or transform existing ones” (Day & Schoemaker, 2000),
or change ”the basis of competition” (Hung & Chu, 2006), etc.
• This conceptualisation inevitably excludes technologies that
may still exert a prominent impact within specific domains
• ‘Scope’ of a technology: few vs. many domains (‘GPT’) of applications

16. Uncertainty and ambiguity
• ‘Uncertainty’ (identified in 6/12 definitions) is generally expressed in terms of the ’potential’
that emerging technologies have for changing the existing ’ways of doing things’ (e.g. Boon &
Moors, 2008; Cozzens et al., 2010)
science & society t
are judged to foster h
the possible outcom
probabilities. In the
this is the formal co
under these condit
tional techniques of
scientifically rigorou
it is also clear that th
risk also implies ci
tainty, ambiguity a
which the reductiv
assessment are not a
Under the con
(Fig 1), we can cha
comes, but the ava
analytical models do
basis for assigning p
these conditions tha
exist” (de Finetti, 19
still exercise subje
treat these as a basi
sis. However, the ch
is that such judgemeFig 1 | Contrasting states of incomplete knowledge,with schematic examples.TSE,transmissible
■ RISK
■ Familiar systems
■ Controlled conditions
■ Engineering failure
■ Known epidemics
■ Transport safety
■ Flood
(under normal conditions)
■ UNCERTAINTY
■ Complex, nonlinear, open systems
■ Human element in causal models
■ Specific effects beyond boundaries
■ Flood under climate change
■ Unassessed carcinogens
■ New variant human pathogens
IGNORANCE ■
Unanticipated effects ■
Unexpected conditions ■
Gaps, surprises, unknowns ■
Novel agents like TSEs ■
Novel mechanisms ■such as endocrine disruption
AMBIGUITY ■
Contested framings, questions, ■assumptions, methods
Comparing incommensurables: ■apples and oranges
Disagreements between ■specialists, disciplines
Issues of behaviour, ■trust and compliance
Interest, language, meaning ■
Matters of ethics and equity ■
NOT problematic
NOT problematic
Problematic
Problematic
Knowledge about
PROBABILITIES
Knowledge about
OUTCOMES
Source: Stirling (2007)

17. … so, what is an emerging technology?

18. An emerging technology is a radically novel and relatively fast growing technology
characterised by a certain degree of coherence persisting over time and with the
potential to exert a considerable impact on the socio-economic domain(s) which is
observed in terms of the composition of actors, institutions and patterns of
interactions among those, along with the associated knowledge production
processes.
Its most prominent impact, however, lies in the future and so in the emergence
phase is still somewhat uncertain and ambiguous.

19. A framework for the
operationalisation of emergence

20. Contemporary analysis Retrospective analysis
Radical
novelty
Contentanalysis of
• news articles
• editorials
• reviews
Citation and co-wordanalyses
• New clusters linkingotherwise weakly connected
clusters (e.g. Furukawa et al., 2015) or citingmore recent
clusters (e.g. Morris et al., 2003)
• Clusters that are new to both the co-citation
and the direct citation model (Small et al., 2014)
Overlay mapping
• Use of new knowledge bases (Rafols et al., 2010)
Relatively
fast growth
Not yet observed in scientometric data Indicators and trend analysis
• Yearly countof documents (includingmodelling)
• ’Bursts of activity’ (Kleinberg, 2002)
• Increasingnumber of authors (Bettencourt et al., 2008)
Citation and co-wordanalyses
• Growth of clusters (e.g. Ohniwa et al., 2010)
Coherence Indicators and trend analysis
• Appearance of abbreviations (Reardon,
2014) and categories (Cozzens et al., 2010)
• Creation of conference tracks,journal SI,
and new journals (Leydesdorff et al., 1994)
Indicators and trend analysis
• Entropy measures (e.g. Watts & Porter, 2003)
• Dense sub-graphs in co-authorshipnetworks (e.g.
Bettencourt et al., 2009)
Citation and co-wordanalyses
• Dense sub-graphs citation/co-wordnetworks (e.g. Yoon et
al, 2010, Furukawa et al., 2015)
Prominent
impact
Not yet observed in scientometric data Impact seems to be taken for granted
Uncertainty
& ambiguity
Measurementchallenges Efforts in measuringuncertainty reduction with Triple-Helix
models (Lucio-Arias & Leydesdorff, 2009),but this area remains
largely unexplored

21. Contemporary analysis Retrospective analysis
Radical
novelty
Contentanalysis of
• news articles
• editorials
• reviews
Citation and co-wordanalyses
• New clusters linkingotherwise weakly connected
clusters (e.g. Furukawa et al., 2015) or citingmore recent
clusters (e.g. Morris et al., 2003)
• Clusters that are new to both the co-citation
and the direct citation model (Small et al., 2014)
Overlay mapping
• Use of new knowledge bases (Rafols et al., 2010)
Relatively
fast growth
Not yet observed in scientometric data Indicators and trend analysis
• Yearly countof documents (includingmodelling)
• ’Bursts of activity’ (Kleinberg, 2002)
• Increasingnumber of authors (Bettencourt et al., 2008)
Citation and co-wordanalyses
• Growth of clusters (e.g. Ohniwa et al., 2010)
Coherence Indicators and trend analysis
• Appearance of abbreviations (Reardon,
2014) and categories (Cozzens et al., 2010)
• Creation of conference tracks,journal SI,
and new journals (Leydesdorff et al., 1994)
Indicators and trend analysis
• Entropy measures (e.g. Watts & Porter, 2003)
• Dense sub-graphs in co-authorshipnetworks (e.g.
Bettencourt et al., 2009)
Citation and co-wordanalyses
• Dense sub-graphs citation/co-wordnetworks (e.g. Yoon et
al, 2010, Furukawa et al., 2015)
Prominent
impact
Not yet observed in scientometric data Impact seems to be taken for granted
Uncertainty
& ambiguity
Measurementchallenges Efforts in measuringuncertainty reduction with Triple-Helix
models (Lucio-Arias & Leydesdorff, 2009),but this area remains
largely unexplored

22. Contemporary analysis Retrospective analysis
Radical
novelty
Contentanalysis of
• news articles
• editorials
• reviews
Citation and co-wordanalyses
• New clusters linkingotherwise weakly connected
clusters (e.g. Furukawa et al., 2015) or citingmore recent
clusters (e.g. Morris et al., 2003)
• Clusters that are new to both the co-citation
and the direct citation model (Small et al., 2014)
Overlay mapping
• Use of new knowledge bases (Rafols et al., 2010)
Relatively
fast growth
Not yet observed in scientometric data Indicators and trend analysis
• Yearly countof documents (includingmodelling)
• ’Bursts of activity’ (Kleinberg, 2002)
• Increasingnumber of authors (Bettencourt et al., 2008)
Citation and co-wordanalyses
• Growth of clusters (e.g. Ohniwa et al., 2010)
Coherence Indicators and trend analysis
• Appearance of abbreviations (Reardon,
2014) and categories (Cozzens et al., 2010)
• Creation of conference tracks,journal SI,
and new journals (Leydesdorff et al., 1994)
Indicators and trend analysis
• Entropy measures (e.g. Watts & Porter, 2003)
• Dense sub-graphs in co-authorshipnetworks (e.g.
Bettencourt et al., 2009)
Citation and co-wordanalyses
• Dense sub-graphs citation/co-wordnetworks (e.g. Yoon et
al, 2010, Furukawa et al., 2015)
Prominent
impact
Not yet observed in scientometric data Impact seems to be taken for granted
Uncertainty
& ambiguity
Measurementchallenges Efforts in measuringuncertainty reduction with Triple-Helix
models (Lucio-Arias & Leydesdorff, 2009),but this area remains
largely unexplored
Indicators of early
emergence (e.g. altmetrics)
STS mixed qualitative-quantitative
approaches to map expectations
(e.g. Borup et al. 2006; van Lente &
Bakker, 2010)
Numerous scientometric approaches
to generate intelligence
Novel data sources
(e.g. funding data)

23. Discussion

24. Discussion
• Scientometric contribution to operationalise the attributes of emergence:
o Techniques are intrinsically more effective for retrospective analyses
o Focus on the detection of what is emerging, rather than on characterising the
potential of what is detected to be emerging (e.g. uncertainty and ambiguity)
o Emergence as an artifact of the used method (models, data, clustering)
• Complementarity between STS and scientometrics traditions:
o STS tradition attempts to address questions of how emergence happens, thus it may
favouring meaningful interpretations of scientometric data
o Scientometrics brings a more robust empirical approach (e.g. statistical inference)

25. Discussion – Future research
• Conceptualisation
o Origins of emerging technologies?
Some technologies acquire a certain momentum and enter the emergent phase, others
do not emerge at all
o When does the emergence phase stop?
Limited knowledge of the end point of the emergence process
• Operationalisation
o Counterfactual sample?
Studies often tend to analyse emerging technologies, without comparing them with a
counterfactual sample of technologies that eventually did not emerge
o Novel data sources
! Publication-full-text (e.g. sentiment analysis)
! Funding data ('uncertainty and ambiguity; relatively fast growth)
! Big data and altmetrics as ’real-time’ data for early detection indicators

26. Conclusions
• Considerable disagreement exists on what is technological emergence and how it should be
operationalised
• Implications for policy-making in the context of emerging technologies (e.g. resource
allocation, creation of research programmes, drawing up of regulations)
• Notwithstanding the fuzziness of the concept of emerging technologies, this study is one of
the first attempts to increase the conceptual clarity on the phenomenon – a necessary
precondition for a coherent and systematic operationalisation of emerging technologies

27. ….thank you
Funded by:
d.rotolo@sussex.ac.uk
@danielerotolo
www.danielerotolo.com
http://dx.doi.org/10.1016/j.respol.2015.06.006
Research Policy 44 (2015) 1827–1843
Contents lists available at ScienceDirect
Research Policy
journal homepage: www.elsevier.com/locate/respol
What is an emerging technology?
Daniele Rotoloa,b,∗
, Diana Hicksb
, Ben R. Martina,c
a
SPRU – Science Policy Research Unit, University of Sussex, Brighton BN1 9SL, United Kingdom
b
School of Public Policy, Georgia Institute of Technology, Atlanta 30332-0345, United States
c
Centre for Science and Policy (CSAP) and Centre for Business Research, Judge Business School, University of Cambridge, Cambridge CB2 1QA,
United Kingdom
a r t i c l e i n f o
Article history:
Received 11 December 2014
Received in revised form 15 June 2015
Accepted 16 June 2015
Keywords:
Emerging technologies
Conceptualisation
Definition
Attributes of emergence
Operationalisation
Detection and analysis
Framework
Scientometrics
Indicators
Science and Technology Studies (STS)
a b s t r a c t
There is considerable and growing interest in the emergence of novel technologies, especially from the
policy-making perspective. Yet, as an area of study, emerging technologies lack key foundational ele-
ments, namely a consensus on what classifies a technology as ‘emergent’ and strong research designs
that operationalise central theoretical concepts. The present paper aims to fill this gap by developing a
definition of ‘emerging technologies’ and linking this conceptual effort with the development of a frame-
work for the operationalisation of technological emergence. The definition is developed by combining
a basic understanding of the term and in particular the concept of ‘emergence’ with a review of key
innovation studies dealing with definitional issues of technological emergence. The resulting definition
identifies five attributes that feature in the emergence of novel technologies. These are: (i) radical novelty,
(ii) relatively fast growth, (iii) coherence, (iv) prominent impact, and (v) uncertainty and ambiguity. The
framework for operationalising emerging technologies is then elaborated on the basis of the proposed
attributes. To do so, we identify and review major empirical approaches (mainly in, although not limited
to, the scientometric domain) for the detection and study of emerging technologies (these include indica-
tors and trend analysis, citation analysis, co-word analysis, overlay mapping, and combinations thereof)
and elaborate on how these can be used to operationalise the different attributes of emergence.
© 2015 Elsevier B.V. All rights reserved.
1. Introduction
Emerging technologies have been the subject of much debate
in academic research and a central topic in policy discussions and
initiatives. Evidence of the increasing attention being paid to the
phenomenon of emerging technologies can be found in the grow-
ing number of publications dealing with the topic and news articles
mentioning emerging technologies (in their headlines or lead para-
graphs), as depicted in Fig. 1. Increasing policy interest in emerging
technologies, however, must be set against a literature where no
consensus has emerged as to what qualifies a technology to be
emergent. Definitions proposed by a number of studies overlap,
but also point to different characteristics. For example, certain def-
initions emphasise the potential impact emerging technologies are
capable of exerting on the economy and society (e.g. Porter et al.,
2002), especially when they are of a more ‘generic’ nature (Martin,
∗ Corresponding author at: SPRU – Science Policy Research Unit, University of
Sussex, Brighton BN1 9SL, United Kingdom. Tel.: +44 1273 872980.
E-mail addresses: d.rotolo@sussex.ac.uk (D. Rotolo),
diana.hicks@pubpolicy.gatech.edu (D. Hicks), b.martin@sussex.ac.uk (B.R. Martin).
1995), while others give great importance to the uncertainty asso-
ciated with the emergence process (e.g. Boon and Moors, 2008) or
to the characteristics of novelty and growth (e.g. Small et al., 2014).
The understanding of emerging technologies also depends on the
analyst’s perspective. An analyst may consider a technology emer-
gent because of its novelty and expected socio-economic impact,
while others may see the same technology as a natural extension
of an existing technology. Also, emerging technologies are often
grouped together under ‘general labels’ (e.g. nanotechnology, syn-
thetic biology), when they might be better treated separately given
their different socio-technical features (e.g. technical difficulties,
involved actors, applications, uncertainties).
The lack of consensus over definitions is matched by an ‘eclec-
tic’ and ad hoc approach to measurement. A wide variety of
methodological approaches have been developed, especially by the
scientometric community, for the detection and analysis of emer-
gence in science and technology domains (e.g. Porter and Detampel,
1995; Boyack et al., 2014; Glänzel and Thijs, 2012). These methods,
favoured, because they take advantage of growing computational
power and large new datasets and allow one to work with more
sophisticated indicators and models, lack strong connections to
well thought out concepts that one is attempting to measure, a basic
http://dx.doi.org/10.1016/j.respol.2015.06.006
0048-7333/© 2015 Elsevier B.V. All rights reserved.